Seamless high-resolution soil moisture from the synergistic merging of the FengYun-3 satellite observations series

Zenodo2024-06-01 更新2026-04-07 收录

土壤水分遥感

地球物理数据融合

数据链接：

https://zenodo.org/doi/10.5281/zenodo.7764786 数据链接链接失效反馈

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资源简介：

These datasets are results from merging three FengYun passive microwave soil moisture observations at a 15kmx15km spatial resolution from 2011 to 2020 with continuous extension as data becomes available. Here, we rely on a merging technique that minimizes mean square error (MSE) using the signal-to-noise ratio (SNRopt) of the input parent products to first merge subdaily soil moisture products into dail averages. From these, these are gap-filled using a Data INterpolating Convolutional Auto-Encoder, DINCAE (FY3_Reoconstructed_*). The advantage of this method is that it comes with error variances(FY3_ErVar_*) for each pixel and time step which are useful for sevral applications.

提供机构：

School of Atmospheric Science & Remote Sensing, Wuxi University, Wuxi 214105, People's Republic of China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China.; Department of Civil Engineering, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-si 17104, Republic of Korea; Planet Labs, Haarlem, the Netherlands; School of Civil and Environmental Engineering, University of New South Wales, Australia; Department of Geology & Geophysics, Bacha Khan University Charsadda, Pakistan; Hydro-Climate Extremes Lab, Ghent University, Ghent, Belgium; Faculty of Defense and Security, Rabdan Academy, Abu Dhabi, United Arab Emirates; GeoHydrodynamics and Environment Research, University of Liège, Liège, Belgium

创建时间：

2024-06-01